Pendekatan Algoritma Apriori Pada Data Mining Untuk Menemukan Pola Belanja Konsumen
Abstract
Data mining is often used in research-related pattern and knowledge of an information is stored in large-scale databases. Today many companies have large amounts of data was stored in the database. The large-scale databases are only used to generate tabular information fo the needs daily of managers. So it can be called rich data but poor information.
Data mining has one assocation method that can generate certain patterns and knowledge of data have an assocate between two itemsets, so it has an if-then property. Algorithm used to produce assocation rule is called apriori.
The result of research represent that the apriori algorithm can work optimally to generate pattern the sales transaction. This research represents transaction frequency{2,3} -> {28} has support 10.5%, confidence 66.6% and {7,8} -> {22} has support 10.5%, confidence 66.6%. Both of rules have frequencies often represent quite high with > 2.
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